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Monthly Traffic Safety Analysis

9,125 CRASHES IN
CONNECTICUT, CT
MAY 2015

In May 2015, Connecticut recorded 9,125 traffic crashes, resulting in 30 fatalities and 3,261 injuries. The most common type of collision was front-to-rear, which accounted for nearly 40% of all reported incidents. These events most frequently occurred on Fridays and during the 4 p.m. afternoon commute hour.

9,125

Total Crash Events

30

Persons Killed

3,261

Persons Injured

10.6%

Hit-and-Run Rate

Note: "Persons Killed" (30) counts individual fatalities across all crash events. "Fatal" in the severity table below (29) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Aggregate counts from crash, person, and vehicle records

964

Hit-and-Run Crashes — May 2015

Based on the initial determination of responding officers, 964 crashes in May 2015 were classified as hit-and-run incidents. This represents 10.6% of all reported crashes during the period.

Vulnerable Road User Casualties

Motor vehicle occupants accounted for the majority of traffic casualties, with 27 motorists killed and 3,118 injured. Among vulnerable road users, 3 pedestrians were killed and 104 were injured. While no cyclists were killed during this period, 39 sustained injuries in crashes.

3

Pedestrians Killed

0

Cyclists Killed

27

Motorists Killed

104

Pedestrians Injured

39

Cyclists Injured

3,118

Motorists Injured

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency peaked on Fridays, which saw 1,787 incidents, and the single busiest hour for crashes was the 4 p.m. hour, with 863 events. Collisions were most common during afternoon commuting hours, with a sustained peak from 3 p.m. to 5 p.m., indicating a strong correlation with daily traffic patterns.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 9,125 total crashes, 74.6% (6,807) resulted in no injuries. The remaining 25.4% of crashes involved at least one possible, minor, or serious injury. There were 29 distinct fatal crashes, which resulted in a total of 30 fatalities, as a single crash can involve more than one death.

Severity is per crash event (most severe injury). 29 fatal crash events resulted in 30 persons killed.

Outcome by Severity (Crash Events)

Fatal29fatal crashes0.3%
Serious Injury123serious injury crashes1.3%
Minor Injury856minor injury crashes9.4%
Possible Injury1,310possible injury crashes14.4%
No Injury6,807no injury crashes74.6%

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Most severe injury per crash record

Road & Environmental Conditions

The vast majority of crashes occurred in ideal driving conditions. Specifically, 92.0% of crashes happened in clear weather, 94.4% on dry road surfaces, and 80.7% during daylight hours. Crashes in the rain accounted for 320 incidents, while those on wet roads numbered 442.

Weather

Clear8,391 (92.7%)
Rain320 (3.5%)
Cloudy293 (3.2%)
Fog, Smog, Smoke34 (0.4%)
Other14 (0.2%)
Blowing Sand, Soil, Dirt1 (0.0%)
Severe Crosswinds1 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Weather condition at time of crash

Lighting

Daylight7,363 (81.3%)
Dark-Lighted1,134 (12.5%)
Dark-Not Lighted347 (3.8%)
Dusk109 (1.2%)
Dawn63 (0.7%)
Dark-Unknown Lighting36 (0.4%)
Other8 (0.1%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Lighting condition field

Road Surface

Dry8,610 (94.8%)
Wet442 (4.9%)
Mud, Dirt, Gravel16 (0.2%)
Other7 (0.1%)
Standing Water6 (0.1%)
Moving Water3 (0.0%)
Sand3 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Road surface condition field

Vehicles & Demographics

Among all persons involved in crashes, the 26-34 age group was the most represented, accounting for 3,860 individuals, followed by the 45-54 age group (3,423). Based on vehicle records, the most frequently involved vehicle makes were Honda (1,956 vehicles), Toyota (1,796), and Ford (1,754).

Top Vehicle Makes (17,385 vehicles)

1
FORD1,754 (10.1%)
2
HONDA999 (5.7%)
3
HOND957 (5.5%)
4
TOYOTA875 (5%)
5
TOYT774 (4.5%)
6
CHEV771 (4.4%)
7
NISS755 (4.3%)
8
NISSAN745 (4.3%)
9
JEEP615 (3.5%)
10
CHEVROLET447 (2.6%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Vehicle unit records

1,524 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (21,984 persons with recorded sex)

Male12,189 (55.4%)
Female9,795 (44.6%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Person-level records linked to crash events

Speed Limit Zones

Roadways with a posted speed limit of 25 mph saw the highest number of crashes, with 2,678 incidents, representing 29.3% of the total. The percentage of crashes within a given speed zone that resulted in a fatality tended to increase with the speed limit. For instance, 0.22% of crashes in 25 mph zones were fatal, while this figure rose to 1.70% for crashes in 65 mph zones.

Fatal crashes by zone: 25 mph: 6 of 2,678 (0.224%) · 35 mph: 3 of 988 (0.304%) · 40 mph: 3 of 534 (0.562%) · 45 mph: 2 of 319 (0.627%) · 50 mph: 3 of 249 (1.205%) · 55 mph: 2 of 851 (0.235%) · 65 mph: 8 of 471 (1.699%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Posted speed limit at crash location

Top Counties

Crash distribution was heavily concentrated in three counties, which together accounted for over 82% of all incidents statewide. Fairfield County recorded the most crashes with 2,831, followed by New Haven County (2,528) and Hartford County (2,183).

Top Counties

1
Fairfield2,831 (31.2%)
2
New Haven2,528 (27.9%)
3
Hartford2,183 (24.1%)
4
New London533 (5.9%)
5
Litchfield343 (3.8%)
6
Middlesex310 (3.4%)
7
Tolland175 (1.9%)
8
Windham158 (1.7%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Top Towns

Analysis by municipality shows that the highest crash volumes occurred in the state's largest urban centers. New Haven had the most incidents with 646 crashes, followed by Hartford with 578, Stamford with 460, and Waterbury with 457.

Top Towns

1
New Haven646 (8.8%)
2
Hartford578 (7.9%)
3
Stamford460 (6.3%)
4
Waterbury457 (6.2%)
5
Bridgeport429 (5.8%)
6
Danbury320 (4.4%)
7
Norwalk317 (4.3%)
8
Fairfield200 (2.7%)
9
Greenwich199 (2.7%)

Showing top 9 of 50 reported. 41 additional (3,746 total) not shown: Meriden, Stratford, West Haven, Bristol, Hamden, New Britain, East Hartford, Manchester, Wallingford, West Hartford, Milford, Middletown, Trumbull, Orange, Westport, Farmington, Wethersfield, North Haven, Norwich, Torrington, Enfield, Southington, New London, Shelton, Darien, Branford, Newtown, Windsor, Groton, Vernon, East Haven, Glastonbury, Wilton, New Milford, Derby, Cromwell, Berlin, Cheshire, Montville, New Canaan, Bloomfield.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Road Class

Among crashes where road class was specified, Local roads accounted for the highest number of incidents with 333. Combined, limited-access highways like Interstates (227 crashes) and Freeways/Expressways (134 crashes) represented 25.0% of these crashes.

Road Class

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Route System

Crashes were split between local and state-maintained roadways. Local roads accounted for 3,705 crashes (43.2%), while state-maintained routes, including State, Interstate, and US Routes, were the location for 4,879 crashes, or 56.8% of the total where the route system was identified.

Route System

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Public vs Private Road

Of the crashes where roadway ownership was recorded, the vast majority occurred on public roads (8,451 incidents). A total of 358 crashes, or 4.1% of this subset, took place on private property such as parking lots or private drives.

Rural vs Urban

Based on the available data classifying crash locations, 1,277 incidents occurred in urban areas. Crashes in rural areas accounted for 166 incidents, representing 11.5% of this classified total.

Rural vs Urban

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Junction Type

A majority of crashes, 6,204 incidents or 68.3%, did not occur at an intersection. Of the crashes that did happen at a junction, four-way intersections were the most common location (1,414 crashes), followed by T-intersections (1,276 crashes).

Junction Type

1
Not at Intersection6,204 (68.3%)
2
Four-Way Intersection1,414 (15.6%)
3
T-Intersection1,276 (14%)
4
Y-Intersection130 (1.4%)
5
L-Intersection32 (0.4%)
6
Five-Point, or More20 (0.2%)
7
Roundabout9 (0.1%)
8
Traffic Circle2

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Run-off-Road / Fixed-Object Strikes

For crashes involving a collision with a fixed object, the most commonly struck items were guardrail faces (180 incidents), utility poles or light supports (175), and curbs (118). Combined, collisions with utility poles and trees accounted for 278 incidents, representing 22.7% of all recorded fixed-object crashes.

Run-off-Road / Fixed-Object Strikes

1
Other Fixed Object (wall, building, tunnel, etc.)220 (17.4%)
2
Guardrail Face180 (14.3%)
3
Utility Pole/Light Support175 (13.9%)
4
Curb118 (9.4%)
5
Tree (standing)103 (8.2%)
6
Other Post, Pole or Support83 (6.6%)
7
Concrete Traffic Barrier65 (5.2%)
8
Embankment44 (3.5%)
9
Mailbox42 (3.3%)

Showing top 9 of 22 reported. 13 additional (232 total) not shown: Traffic Sign Support, Cable Barrier, Fence, Ditch, Other Traffic Barrier, Guardrail End, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Bridge Overhead Structure, Impact Attenuator/Crash Cushion, Culvert, Traffic Signal Support, Bridge Rail, Bridge Pier or Support.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 10,979 of the 17,385 vehicles recorded. Sport utility vehicles (2,901) and pickups (1,142) were also frequently involved. Notably, 388 medium or heavy trucks, 190 motorcycles, and a combined 141 school or transit buses were documented in these incidents.

Vehicle Type

1
Passenger Car10,979 (64.2%)
2
(Sport) Utility Vehicle2,901 (17%)
3
Pick Up1,142 (6.7%)
4
Passenger Van627 (3.7%)
5
Medium / Heavy Trucks (more than 10,000 lbs (4,536 kg))388 (2.3%)
6
Other274 (1.6%)
7
Cargo Van (10,000 lbs/4,536 kg or less)193 (1.1%)
8
Motorcycle190 (1.1%)
9
Other Light Trucks (10,000 lbs (4,536 kg) or less)184 (1.1%)

Showing top 9 of 18 reported. 9 additional (225 total) not shown: School Bus, Transit Bus, Moped, Other Bus, All Terrain Vehicle (ATV), Low Speed Vehicle, Motor Home, Motor Coach, Golf Cart.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Vehicle unit records

Traffic Control Device

The majority of vehicles in crashes were at locations with no traffic control device, accounting for 11,610 vehicles (67.1% of those with specified controls). Locations with a traffic signal were the site of crashes involving 4,136 vehicles, while intersections controlled by a stop sign involved 1,119 vehicles.

Traffic Control Device

"Other" combines 5 smaller categories (40 records): Marked Uncontrolled Crosswalk (14), Warning Sign (14), School Zone Sign/Device (7), Railway Crossing Device (3), Pedestrian Button (2).

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Vehicle unit records

Vulnerable Road Users & Motorcycles

Among crashes involving motorcyclists or vulnerable road users, motorcyclists were the largest group with 183 incidents. There were 109 crashes involving pedestrians and 48 involving bicyclists. Combined, pedestrians and bicyclists were involved in 157 crashes, representing 46.2% of this specific crash subset.

Driver Contributing Action

The most common contributing action cited for drivers was 'Followed Too Closely,' which was noted for 2,842 drivers. Other frequent actions included 'Failed to Keep in Proper Lane' (1,329 drivers) and 'Failed to Yield Right-of-Way' (875 drivers).

Driver Contributing Action

1
No Contributing Action7,638 (49%)
2
Followed Too Closely2,842 (18.3%)
3
Failed to Keep in Proper Lane1,329 (8.5%)
4
Failed to Yield Right-of-Way875 (5.6%)
5
Improper Backing598 (3.8%)
6
Other Contributing Action473 (3%)
7
Improper Turn325 (2.1%)
8
Ran Off Roadway302 (1.9%)
9
Improper Passing264 (1.7%)

Showing top 9 of 19 reported. 10 additional (926 total) not shown: Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner, Ran Stop Sign, Ran Red Light, Swerved or Avoided Due to Wind, Slippery Surface, Motor Vehicle, Object, Non-Motorist in Roadway, etc., Operated Motor Vehicle in Reckless or Aggressive Manner, Over-Correcting/Over-Steering, Wrong Side or Wrong Way, Disregarded Other Traffic Sign, Disregarded Other Road Markings, Overtaking Cyclist.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Person-level records linked to crash events

Driver Condition

While most drivers were recorded as 'Apparently Normal,' several contributing conditions were noted. A total of 263 drivers were suspected of being under the influence of medications, drugs, or alcohol. Additionally, 161 drivers were identified as asleep or fatigued, and 115 were noted as being in an emotional state.

Driver Condition

1
Apparently Normal14,645 (95.5%)
2
Under the Influence of Medications/Drugs/Alcohol263 (1.7%)
3
Asleep or Fatigued161 (1%)
4
Emotional (depressed, angry, disturbed, etc.)115 (0.7%)
5
Other68 (0.4%)
6
Ill (sick), Fainted47 (0.3%)
7
Physically Impaired39 (0.3%)

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Person-level records linked to crash events

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was moving straight ahead, which was the case for 7,749 vehicles (44.6%). A significant number of vehicles were either stopped in traffic (1,950) or in the process of slowing (1,297) immediately prior to the collision.

Pre-Crash Driver Action

1
Straight Ahead7,749 (45.4%)
2
Stopped in Traffic1,950 (11.4%)
3
Slowing1,297 (7.6%)
4
Turning Left1,237 (7.3%)
5
Parked1,214 (7.1%)
6
Backing770 (4.5%)
7
Turning Right624 (3.7%)
8
Changing Lanes549 (3.2%)
9
Negotiating a Curve475 (2.8%)

Showing top 9 of 17 reported. 8 additional (1,186 total) not shown: Overtaking/Passing, Entering Traffic Lane, Other, Leaving Traffic Lane, Wrong way (or Wrong Side), Making U-Turn, Overtaking/Passing Cyclist, Traveling in Bike Lane.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Vehicle unit records

Point of Impact

The front of the vehicle was the most common point of initial impact, recorded for 5,010 vehicles, or 28.8% of those involved. The rear of the vehicle was the second most frequent impact point, accounting for 3,738 vehicles (21.5%).

Point of Impact

"Other" combines 9 smaller categories (2,650 records): Sector 2 (NorthEast) in the 12-point Clock Diagram (609), Sector 9 (West) in the 12-point Clock Diagram (511), Sector 3 (East) in the 12-point Clock Diagram (462), Sector 8 (SouthWest) in the 12-point Clock Diagram (399), Sector 4 (SouthEast) in the 12-point Clock Diagram (349), Non-Collision (144), Top (122), Undercarriage (34), Cargo loss (20).

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Vehicle unit records

Pedestrian/Cyclist Action

Among the 152 instances where a pedestrian's action was documented, 72 were classified as 'No Improper Action.' For those with contributing actions, the most common were 'Dart/Dash' into the roadway (18 instances), being in the roadway improperly (17), and failure to yield the right-of-way (12).

Pedestrian/Cyclist Action

1
No Improper Action72 (47.4%)
2
Dart/Dash18 (11.8%)
3
In Roadway Improperly (Standing, Lying, Working, Playing)17 (11.2%)
4
Failure to Yield Right-Of-Way12 (7.9%)
5
Failure to Obey Traffic Signs, Signals, or Officer11 (7.2%)
6
Inattentive (Talking, Eating, etc.)6 (3.9%)
7
Wrong-Way Riding or Walking5 (3.3%)
8
Other4 (2.6%)
9
Not Visible (Dark Clothing, No Lighting, etc.)3 (2%)

Showing top 9 of 12 reported. 3 additional (4 total) not shown: Improper Turn/Merge, Disabled Vehicle Related (Working on, Pushing, Leaving/Approaching), Use of Electronic Device.

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Non-motorist records linked to crash events

Manner of Collision

The most prevalent type of collision was 'Front to rear,' which accounted for 3,642 incidents, or 39.9% of all crashes with a specified manner. Angle collisions were the second most common type with 1,570 incidents (17.2%), followed by same-direction sideswipes at 1,231 incidents (13.5%).

Manner of Collision

"Other" combines 1 smaller categories (79 records): Front to front (79).

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Person Type

Of the 23,316 individuals involved in crashes, the majority were drivers (16,288 persons, or 69.9%). Passengers made up the next largest group with 5,764 individuals (24.7%). The data also includes 115 pedestrians and 48 bicyclists.

Person Type

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Person Injury Severity

Across all 23,316 people involved in crashes, 19,088 (81.9%) were not injured. A total of 3,261 individuals sustained injuries of possible, minor, or serious severity. Thirty individuals, or 0.13% of all persons involved, suffered fatal injuries.

Person Injury Severity

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Occupant Safety Equipment

Among motor vehicle occupants where safety equipment use was documented, 15,950 were reported as using a shoulder and lap belt. A total of 492 occupants were recorded as not using any restraint system. The data also noted the use of forward-facing child restraints in 463 cases.

Occupant Safety Equipment

"Other" combines 3 smaller categories (166 records): Other (60), Booster Seat (55), Child Restraint, Type Unknown (51).

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Person-level records linked to crash events

Vehicles Per Crash

The majority of crashes involved two vehicles, accounting for 6,983 incidents (76.5% of the total). Single-vehicle crashes were the next most common scenario, with 1,576 incidents (17.3%). Crashes involving three or more vehicles numbered 565, with one incident involving seven vehicles.

Vehicles Per Crash

"Other" combines 1 smaller categories (1 records): 7 (1).

Source: Connecticut Crash Data · Csv Open Data · 2015-05-01 to 2015-05-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Connecticut Crash Data, accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Csv Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2015-05-01 through 2015-05-31
  • Report generated: August 20, 2026

Data Coverage

  • Reporting period: 2015-05-01 through 2015-05-31 (31 days)
  • Geographic scope: connecticut, CT
  • Total crash records analyzed: 9,125
  • Total persons involved: 23,316
  • Total vehicles involved: 17,385

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "connecticut, CT Crash Intelligence Report: May 2015." Published August 20, 2026. Reporting period: 2015-05-01 to 2015-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-2015-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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